Fuzzy portfolio selection using genetic algorithm
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on intelligent systems for financial engineering and computational finance
Computers & Mathematics with Applications
Modeling Fuzzy DEA with Type-2 Fuzzy Variable Coefficients
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Optimizing material procurement planning problem by two-stage fuzzy programming
Computers and Industrial Engineering
Type-2 fuzzy variables and their arithmetic
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Modeling data envelopment analysis by chance method in hybrid uncertain environments
Mathematics and Computers in Simulation
Fuzzy portfolio selection problems based on credibility theory
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Expected value of fuzzy variable and fuzzy expected value models
IEEE Transactions on Fuzzy Systems
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This paper adopts the spread of fuzzy variable as a new criteria in practical risk management problems, and develops a novel fuzzy expectation-spread (E-S) model for portfolio optimization problem. Since the spread is defined by Lebesgue-Stieltjes (L-S) integral, its computation for general fuzzy variables is a challenge issue for research, and usually depends on approximation scheme and soft computing. But for frequently used trapezoidal and triangular fuzzy variables, the spread can be represented as quadratic functions with respect to fuzzy parameters. These new representations facilitate us to turn the proposed E-S model into its equivalent parametric programming problem. As a consequence, given the fuzzy parameters, the E-S model becomes a quadratic programming problem that can be solved by general purpose software or conventional optimization algorithms. Finally, we demonstrate the developed modeling idea via two numerical examples.